analyse-coverage

Analyze coverage.json data and generate a Markdown coverage analysis report.

31|1|Updated Mar 28, 2026
One-click install
npx skills add https://github.com/Ascend/agent-skills --skill analyse-coverage
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analyse-coverage
Source: https://github.com/Ascend/agent-skills/tree/main/skills/mindspeed-llm-auto-ut-skills/skills/analyse-coverage
Command: npx skills add https://github.com/Ascend/agent-skills --skill analyse-coverage

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

分析测试覆盖率盲区,帮助开发团队识别未覆盖的代码区域并生成系统化的覆盖率分析报告。

Core Features & Use Cases

  • 自动分析覆盖率数据并生成覆盖率分析报告
  • 解析 COVERAGE/report/coverage.json,提取函数覆盖率、执行/缺失行等信息
  • 根据覆盖率对函数进行分组(低/中/高覆盖率)并输出改进建议
  • 生成 COVERAGE/report/coverage_analysis_report.md,用于团队评审和改进

Quick Start

运行覆盖率分析流程以生成 COVERAGE/report/coverage_analysis_report.md。

Frequently Asked Questions about analyse-coverage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a coverage.json file to find untested Python functions?

To analyze coverage.json data, this Skill parses the file to extract execution and missing line data, categorizing Python functions into low, medium, and high coverage groups. It outputs a coverage_analysis_report.md detailing testing blind spots.

What is the best way to generate a code coverage report for team review?

The best way to generate a code coverage report is by parsing coverage.json data to categorize function coverage levels. This Skill produces a comprehensive Markdown report highlighting blind spots and improvement suggestions for team evaluations.

Does this coverage analysis tool require any specific dependencies?

No dependencies are required to run this coverage analysis tool. It supports Python-based analysis natively and only requires a valid COVERAGE/report/coverage.json file as input to identify testing blind spots and generate reports.

How do I categorize functions by coverage rate in my testing project?

To categorize functions by coverage rate, the Skill analyzes coverage.json data and groups Python functions into low, medium, and high coverage buckets. It generates a coverage_analysis_report.md with these categorizations for team review.

What input format is needed to identify testing blind spots in software projects?

Identifying testing blind spots requires a COVERAGE/report/coverage.json file as input. The Skill parses this coverage data to extract function execution data and missing lines, producing a Markdown analysis report for evaluating code health.